In this edition of linkz the theme goes from exploitation to infection to detection. Some linkz discussed include: providing clarity about my exploit artifacts, a spear-phishing write-up, a malware analysis checklist, and thoughts about automated vs in-depth malware analysis.

Picking Vulnerabilities

Over the past year I’ve been conducting research to document attack vector artifacts. Vulnerabilities and the exploits that target them are one component to an attack vector. Some may have noticed I initially focused most of my efforts on vulnerabilities present in Adobe Reader and Java. I didn’t pick those applications by flipping a coin or doing “eeny, meeny, miny, moe”. It is not a coincidence I’m seeing exploit artifacts left on systems that target those applications. This has occurred because I pick vulnerabilities based on the exploits contained in exploit packs.

Notice how many Java and Adobe vulnerabilities are on the list. Maybe now it’s a little more clearer why I wrote about Adobe/Java exploits and why I wasn’t surprised when system after system I keep finding artifacts associated with those exploits. The spreadsheet shows what applications exploit packs are targeting. I’ve been using the document as a reference to help me decide what exploit artifacts to document. Down the road when I start looking into Word, Excel, and flash exploits then at least there will be a little more clarity as to what I’m choosing to document.

Another Adobe Flash Exploit

Since I mentioned both Adobe, flash, and exploit in the same paragraph then I might as well mention them in the same sentence. Zscaler ThreatLab blog recently posted Adobe Flash “SWF” Exploit still in the Wild. The short write-up discusses how a vulnerability in Adobe flash (CVE-2011-0611) is being exploited by embedding a .swf file into Microsoft Office documents or html pages. I wanted to highlight one specific sentence "this exploit code embeds a “nb.swf” flash file into a webpage, which is then executed by the Adobe Flash player". That one sentence identified numerous potential artifacts one could find on a system indicating this attack vector was used. First there will be Internet browser activity followed by a flash file being accessed. The system may then show a swf file being created in a temporary folder and there may also be indications that Adobe flash executed shortly thereafter. The write-up doesn't go into what artifacts are left on a system since its focus is on how the attack worked. At this point those potential artifacts are just that potential. However, flash exploits are third on my list for what I'm going to start documenting. It shouldn’t come as a surprise by now that Mila’s spreadsheet also shows a few exploit packs targeting the flash vulnerability.

Walking through a Spearphishing Attack

The Kahu Security blog post APEC Spearfish does an excellent job walking the reader through an actual spearphishing attack. The spearphish was an email targeted at a single individual and contained a malicious PDF attachment. There was a flash object in the PDF file that exploited a vulnerability in Adobe Flash Player (yup … CVE-2011-0611). The end result was a malware infection providing backdoor access for the attackers. The post isn't written from the DF perspective; it doesn't outline the artifacts on a system indicating a spearphish occurred or a flash exploit caused the malware infection. However, it does a great job breaking down the attack from the person receiving the email to the PDF file launching to malware getting dropped. One image I liked was the one showing "what’s happening behind the scenes" since it helps DF readers see the potential artifacts associated with the method use to infect the system.

Finding Malware Checklist

Last month Harlan posted about his experience at PFIC 2011. At the end of his post he shared his Malware Detection Checklist which outlines the examination steps to locate malware on the system. I think it’s a great list and I like how the checklist is focused on a specific task; finding malware. I added some of the activities in Harlan’s checklist to my own because I either wasn’t doing it or I wasn’t deliberate about doing it. One step I wasn’t doing was scanning for packed files and thinking about it I can see how it can help reduce the amount of binaries to initially examine. On the other end, one step I wasn’t deliberate about was examining the user’s temporary directories. I was examining these directories through timeline analysis but I wasn’t deliberate about searching the entire folder for malware or exploit artifacts.

The cool thing about Harlan’s checklist is that he already did the heavy lifting. He put together a process that works for him (including the tools he uses) and is sharing it with the community. It wouldn’t be hard for anyone to take what he already did and incorporate it into their own examination process. Plus, his blog post mentioned the checklist came from Chapter 6 in WFA 3 so the book (once released) can be a reference to better understand how to go about finding malware on a system.

Another Angle at Finding Malware

Along the same lines about trying to identify malware on a system Mark Morgan over at My Stupid Forensic Blog discussed the topic in his post How to Identify Malware Behavior. Mark first proceeded to explain the four main characteristics of malware which are: an initial infection vector, malware artifacts, propagation mechanism, and persistence mechanism. (Harlan also described these characteristics on his malware webpage). The characteristics are important since there artifacts associated with them and those artifacts can help identify the malware. Mark provided a great example about how the persistence mechanism played a role in one of his cases. He even went on to explain a few different ways to track down malware and its persistence mechanism.

Analyzing Malware

At some point during the examination malware will be identified on the system. Some can just start analyzing the malware since they are fortunate enough to know how to reverse engineer its functionality or know someone who can. The rest of us may not have that luxury so we should just upload the sample to online scanners such as VirusTotal or Sandboxes right? Well, I wouldn’t be too fast in pulling the trigger without understanding the risks involved. The Hexacorn blog put together the excellent post Automation vs. In-depth Malware Analysis. In the author’s own words the "post is my attempt to summarize my thoughts on the topic of both automated malware analysis in general and consensual submission of files to a web site owned by a third party". There are times when submitting samples to a third party service are not the best choice to make. I first learned about the risk when a discussion occurred in the Win4n6 group sometime ago but the post goes into more depth. For anyone dealing with malware and considering using third party services -such as VirusTotal or ThreatExert - than I highly recommend reading this post to help you make an informed decision.

On a side note, the Hexacorn blog started to post forensic riddles every Friday followed by posting the answer every Monday. The riddles are entertaining and educational. My stat count so far is zero for two (I wasn’t even close).

There are different ways to spread malware. Email, instant messaging, removable media, or websites are just a few options leveraged to infect systems. One challenge when performing an examination is determining how the malware ended up on the system which is also referred to as identifying the malware’s initial infection vector (IIV). A few obstacles in determining the IIV is that a system changes over time: files are deleted, programs are installed, temporary folders are emptied, browser history is cleared, or an antivirus program cleaned the system. Every one of those obstacles may hinder the examination. However, they don’t necessary result in not being able to narrow down the IIV since some artifacts may still be present on the system pointing to the how.

There are various reasons provided why an examination isn’t performed on a malware infected system to locate the IIV. I first wanted to point out why taking the time to find the IIV is beneficial instead of focusing on the reasons why people don’t. The purpose of the root cause analysis is to identify the factors lead up to the infection and what actions need to be changed to prevent the reoccurrence of a similar incident. If the infected system is just cleaned and put back into production then how can security controls be adjusted or implemented to reduce malware infecting systems in a similar manner? Let’s see how this works by skipping the root cause analysis and placing blame on a user opening a SPAM email. A new security awareness initiative educates employees on not opening SPAM email which does very little if the malware was a result of a break down in the patch management process. Skipping figuring out the IIV is not only a lost opportunity for security improvements but it prevents knowing when the infection first occurred and what data may have been exposed. This applies to both organizations and individuals.

Determining how the malware infected a system is a challenge but that's not a good enough reason to not try. It may be easier to say it can’t be done, takes too much resources or it's not worth it since someone (aka users) never listen and did something they weren’t suppose to. As a learning opportunity I’m sharing how I identified the initial infection vector in a recent examination by showing my thought process and tool usage.

First things first… I maintain the utmost confidentiality in any work I perform whether if it’s DFIR or vulnerability assessments. At times on my blog I write detailed posts about actual examinations I performed and every time I’ve requested permission to do so. This post is no different. I was told I can share the information for the greater good since it may help educate others in the DFIR community who are facing malware infected systems.

Background Information

People don’t treat me as their resident “IT guy” to fix their computer issues anymore. They now usually contact me for another reason because they are aware that I’ve been cleaning infected computers for the past year free of charge. So it’s not a strange occurrence when someone contacts me saying their friend/colleague/family member/etc appears to be infected with a virus and needs a little help. That’s pretty much how this examination came about and I wasn’t provided with any other information except for two requests:

* Tell them how the infection occurred so they can avoid this from happening again

* Remove the viruses from the computer

Investigation Plan

The methodology used throughout the examination is documented on the jIIr Methodology Page. I separated the various system examination steps into the first three areas listed below.

1. Verify the system is infected 2. Locate all malware present on the system 3. Identify the IIV 4. Eradicate the malware and reset any system changes

I organized the areas so each one will build on the previous one. My initial activities were to verify that the system was actually infected as opposed to the requester interpreting a computer issue as an infection. To accomplish this I needed to locate a piece of malware on the system either through antivirus scanning or reviewing the system auto-run locations. If malware was present then the next thing I had to do was locate and document every piece of malware on the computer by: obtaining general information about the system, identifying files created around the time frame malware appeared, and reviewing the programs that executed on the system. The examination would require since the technique excels at highlighting malware on a system. The third area and the focus of this post was to identify the initial infection vector. The IIV is detected by looking at the system activity in the timeline around the timeframe when each piece of malware was dropped onto the system. The activity can reveal if all of the malware is from the same attack or if there were numerous attacks resulting in different malware getting dropped onto the system. The final area is to eradicate every malware identified.

Note: Some activities were conducted in parallel to save time. To make it easier for people to follow my examination I identified each activity with the symbol <Step #>, the commands I ran are in bold, and registry and file paths are italicized.

Verifying the Infection

The computer’s hard drive was connected to my workstation and a software write blocker prevented the drive from being modified. I first reviewed the master boot record (MBR) to see the drive configuration I was dealing with and to check for signs of MBR malware <Step 1>. I ran the Sleuthkit command: mmls.exe -B \\.\PHYSICALDRIVE1 (the -B switch shows the size in bytes). There was nothing odd about the hard drive configuration and I found out that additional time was needed to complete the examination since I was dealing with a 500 GB hard drive. To assist with identifying known malware on the system I fired off a Kaspersky antivirus scan against the drive <Step 2>.

Knowing the antivirus scan was going to take forever to complete I moved on to checking out the system’s auto-runs locations for any signs of infection. The Sysinternals AutoRuns for Windows utility was executed against the Windows folder and the only user profile on the system <Step 3>. In the auto-runs I was looking for unusual paths launching executables, misspelled file names, and unusual folders/files. It wasn’t long before I came across an executable with a random name in the HKCU\SOFTWARE\Microsoft\Windows NT\CurrentVersion\Winlogon\Shell registry key.

The HKCU\Software\Microsoft\Windows\CurrentVersion\Run registry key also listed under Auto-runs Logon tab showed that the C:\Users\John_Doe\AppData\Roaming folder had more than just one randomly named executable. The key also showed an additional location which was the C:\Users\John_Doe\AppData\Roaming\Microsoft folder.

I added the hard drive as an evidence item in FTK Imager v3 to review the folders and executables identified by the Auto-runs utility <Step 4>. I noticed there were two additional executables located directly underneath the Roaming folder with the names iexplore.exe and java.exe. Both files had the same MD5 hash e4c2a000e715d16ec25e2b0a0fb3532f so to confirm the infection I searched for the hash in the Malware Analysis Search custom Google search. There was one search hit for VirScan.org and a few scanners flagged the file as malware (Kaspersky identified it as Trojan.Win32.FakeAV.emha). I followed the similar process to confirm that the other executables were malware as well. At this point I no longer needed the antivirus scan to finish since the infection was verified through other means. Before I moved onto manually locating all malware on the system I needed to document what my timeframe of interest was. I looked at the last modification times and creation times for all the folders/files I found. The rough timeframe spanned over a few days: from 10\13\2011 1:29:34 AM to 10/08/11 11:38:48PM. The picture below shows the last modification times for a few folders in the C:\Users\John_Doe\AppData\Roaming folder.

Locating All Malware on the System

After I verified the system was in fact infected I then proceeded to locate and document every piece of malware. First I had to shed light on the system’s configuration since it would impact how I performed my analysis <Step 5>. I used my regripper-general-os-info.bat batch file to run RegRipper against the system’s registry hives including the one profile’s NTUSER.dat hive. Below I highlighted some information and to the right of the arrow are quick notes about its significance.

* Operating system was Windows 7 Home Premium <= affected what artifacts are available and where they are located

* Default browser plugin showed the default browser was Internet Explorer <= system had two web browsers (Chrome was the other) so my initial focus is on the artifacts from the default one

* Listsoft registry key showed McAfee <= McAfee antivirus software was on the system and its logs may show additional information about the infection.

I opted for the timeline analysis technique to locate all malware on the system and the general information obtained about the system helped to narrow down my artifact list to incorporate into my timeline. Building a timeline on a 500 GB hard drive was going to take some time so I looked at the McAfee logs before tying up my workstation <Step 6>. I exported the McAfee logs with FTK Imager and reviewed them using Notepad ++. The last entry in the log occurred at 10/16/2011 6:50:09 PM and it logged that the file "C:\windows\system32\consrv.DLL" was detected as Generic.dx!bbd4. The next entry didn’t occur until 10/12/11 but there were numerous log entries leading right up until 10/08/11. A few detections included Generic Dropper!1cj, DNSChanger!fa, and Artemis!E4C2A000E715 and they were for files located the folders C:\Users\John_Doe\AppData\Local\Temp\, C:\Windows\assembly\tmp\, and C:\windows\syswow64\. The flurry of McAfee detections for files other than cookies stopped at 10/8/2011 11:37:38 PM as shown in the picture below.

The McAfee log identified potential additional malware on the system and expanded my timeframe to 10/16/2011 6:50:09 PM to 10/08/11 11:37:38 PM. A significant piece of information the log highlighted was Internet activity occurred just before the first detection. I leverage the timeline analysis technique for the rest of the examination. I created a timeline by incorporating the following artifacts: event logs (evtx), registry hives (system, software, and ntuser), link files (win_link), prefetch files (prefetch), Internet Explorer history (iehistory), and the Master File Table (mft) <Step 7>. I ran the following command but replaced the plugin and file path for each desired artifact: log2timeline.pl -f evtx -w timeline.csv E:\Windows\System32\winevt\Logs\Application.evtx. Once my timeline was built I then I started my search for all malware on the system.

Identify the IIV

Locating all malware present on the system and identifying the IIV are not separate activities when I perform timeline analysis. The only reason I separated them was to make it easier to explain my thought process. In actuality the two go hand in hand. Each time a piece of malware is located the system activity around the malware is examined to determine what contributed to the malware being created. Approaching timeline analysis in this manner will help determine if the malware is from the one attack or multiple attacks at different points in time. I review timelines working backwards in time since I find that it’s easier to spot the IIV. Each time I come across a file that could be malicious I first review the file’s header (in this examination I used FTK Imager), perform searches for the file’s MD5 hash (search order is Malware Analysis Search, VirusTotal, and then Google), and at times if the hash search results in no hits and the file type is of interest then I may upload the file to VirusTotal to see if it’s detected. I continue this process in the timeline until I reach the point where the malware activity stops and that’s usually where the IIV is located.

To assist with confirming malicious files I used FTK Imager to export a file hash list for the entire hard drive <Step 8>. It’s a lot easier to already have files’ hashes on hand then it is to calculate the hash each time I come across a new file. I started working my timeline keeping in mind everything I found including the timeframe 10/16/2011 6:50:09 PM to 10/08/11 11:37:38 PM. Besides the timestamps that were not accurate (reflects activity in future) the timeline ended on 10/16/2011 so that is where I started my analysis. I first saw the consrv.dll file detected by McAfee but there were no artifacts around the malware indicating it was the result of a different attack.

After 10/16/11 the next activity started appearing in the timeline on 10/12/11. I found the same thing; more malware and artifacts associated with malware but no artifacts indicating an attack occurred.

I kept working the timeline going backwards in time. I kept finding more malware and malware artifacts but nothing pointing to an IIV explaining how the malware got onto the system. I finally reached the earliest time I noted which was 10/08/11 11:37:38 PM. There was a lot of activity involving files with similar names to the ones reflected in the McAfee log file.

I continued working backwards until I saw no more activity involving the C:\Windows\assessmbly\tmp\U\ folder which is shown in the screenshot below. The U folder was created on the system at the same time as a file resembling a configuration file. One line in the file was srv=hxxps://212.36.9.52/ and my research showed the address appeared in a blacklist and the spsyeyetracker IP blocklist. The activity just before the U folder and configuration file were created was an executable named dbywqomgec (MD5 hash a70e5c48612159b3e936d7e478f4d451) appearing in the John_Doe’s temp folder. VirusTotal showed a few antivirus programs identified the file as a dropper (Microsoft detection was TrojanDropper:Win32/Sirefef.B). Afterwards I analyzed the file with ThreatExpert to see what changes the malware caused.

The activity on the system before the dropper (MD5 hash a70e5c48612159b3e936d7e478f4d451) appeared on the system was a file showing up in the Java cache folder as shown below.

I previously discussed the forensic significance Java index files provide in the post (Almost) Cooked Up Some Java. I exported the Java index file 46e770f3-38b55d85.idx with FTK Imager and looked at the file with Notepad ++. The file’s contents are shown below.

The index file 46e770f3-38b55d85.idx showed a few interesting tidbits. First the file 46e770f3-38b55d85 was downloaded from the URL hxxp://www.seyminck.com/FFFO009/560[dot]gif which had the IP address 212.95.55.40. Secondly, the URL indicated the file was a gif image but the index recorded the file as an application. I checked the file 46e770f3-38b55d85 (MD5 hash 2e833ac26483aaad13a8051bc857ef15) header and it was indeed an executable since the file started with MZ. I analyzed the file with ThreatReport and it was identified as a dropper (Microsoft detection was TrojanDropper:Win32/Sirefef.B). The IIV still wasn’t located so I looked at the activity just before the dropper appeared in the Java cache. The activity showed at the same time another duplicate of the dropper (MD5 hash 2e833ac26483aaad13a8051bc857ef15) appeared in the John_Doe’s temp folder with the file name 0.945837921339929.exe. Four seconds beforehand a file appeared in the Java cache folder which can be seen below highlighted in red.

The Java index file 25e8c780-5c17647b.idx was exported with FTK Imager and read with Notepad ++. The information contained in the index showed that a Java archive file was downloaded from the URL hxxp://www.seyminck(dot)com/FFFO009/RRo/realestate (IP address 212.95.55.40). The Java archive came from the same domain and IP address as the executable located in the Java cache folder. I exported the Java archive 25e8c780-5c17647b (MD5 hash 6b478de65071d94c670a0bfa369a7890) and confirmed the file was a Jar file by examining it with JD-GUI. The MD5 hash search didn’t result in any hits so I uploaded the file to VirusTotal and only 2 out of 42 antivirus products detected it as an exploit. I wanted to know if Java actually executed around the time the exploit appeared in the cache. I exported and reviewed the Java log file C:\Users\John_Doe\AppData\Local\Temp\java_install_reg.log and the log showed Java did in fact execute.

The last piece I needed to identify the IIV was to determine what delivered the exploit to the system. The activity on the system before the exploit answered that question as shown below.

There was a PrivacIE entry for seyminck(dot)com/FFFO009/RRo/*87354602 which means the exploit came from third party content being displayed on a website. The PrivacIE entry was mixed in with activity resembling advertisements from the user searching for someone on peoplefinder and whitepages websites. I continued working backwards in the timeline but there was no more malware activity. The IIV was identified. A user was surfing the Internet when a website visited was hosting third party content which resulted in a successful drive-by download targeting a Java vulnerability.

More Information about the IIV

The Java archive 25e8c780-5c17647b (MD5 hash 6b478de65071d94c670a0bfa369a7890) didn’t have to be examined closer in order to identify the IIV. However, I wanted to better understand how to examine Jar files since they may provide more information about the IIV and help explain some files found on the system. I debated if I should put this section in another blog post because I didn’t want people to think this activity had to be done in order to figure out the IIV. I opted to include the information since it sheds light on what occurred when the exploit was downloaded.

The code in the Jar file was obfuscated to conceal its purpose. I reached out to the Win4n6 group about any methods to automate analyzing Jar files with obfuscated code. A few members pointed me to Java de-obfuscation tools and I’m still in the process of trying to learn how to use them. Another member mentioned that Java obfuscation appears to be not making analysts’ life difficult, but to evade detection by antivirus. The person went on to say the obfuscation is usually weak so it’s relatively simple to de-obfuscate. My first reaction was it may be simple for Java programmers but it seemed impossible to me; I know nothing about Java besides the artifacts left by Java exploits. I took a shot at manually trying to see what the Jar file did by focusing on trying to follow the logic associated the variables, class methods, and functions in the code (I don’t know the Java syntax so if I butcher the names of things such as functions then you know why).

I opened the Java archive 25e8c780-5c17647b in JD-GUI and looked at the manifest file to see the wall Java class gets executed first.

I extracted the Java source code by using the “Save All Sources” option in JD-GUI. I started reviewing the obfuscated source code in the Wall Java class when I saw two lines of code making a call to the Java method Muuum.kjdhfdkjg or Muuum.idufhidufh. For those who don’t know what a Java method is: it’s basically going to the Muuum class and executing the code listed under the method kjdhfdkjg or idufhidufh.

I followed the code to the Muuum class file and found out its purpose was to set a variable to contain an URL. Two variables are set to contain part of the URL and they are then used to build the entire URL. One URL that is built is hxxp://www.seyminck.com/ FFFO009 /560[dot]gif and this was the URL I found in the Java index 46e770f3-38b55d85.idx showing it was where the executable file 46e770f3-38b55d85 (MD5 hash 2e833ac26483aaad13a8051bc857ef15) came from. The screenshot below shows the URL being put together.

I went back to the Wall class and kept reading the code until I came across the first Java function as shown below. The Inputstream function reads data and the data being read was coming from the Java method Kkdjfhgdkfjhgkdfjhgkkkkkkkkkkkk.sodarifhsdoiufhdoiufg86fetgfyusgfyudif. I highlighted the Inputstream function in green while the Java method is highlighted in red.

The followed the code to the sodarifhsdoiufhdoiufg86fetgfyusgfyudif method. The method set the variable URL to contain the value contained in variable s3 which the Wall Java class passed to the method. The method ended with by returning a call to another method in the Kkdjfhgdkfjhgkdfjhgkkkkkkkkkkkk class as highlighted in red below.

Next I went to the mmmm3 method which is pictured below. The first function InputStream sets the URL to read from while the second function Openstream reads the URL stored in the URL variable. I couldn’t find the code that resulted in the URL variable containing the domain hxxp://www.seyminck[dot]com. However, this was the URL the method was reading from becaue the Jar file didn’t reference any other websites. The method returns to the Wall class the data read from the URL.

I went back to the Wall class and continued to follow the code. The next portion I picked up on is the data read from the URL was saved to a file with an exe extension. The picture below shows the code that accomplished this and I highlighted a few areas to make it easier to see. The variable ufy highlighted in the first red box was set to contain a string with a random number ending in .exe. The next variable iioi655er5w5 (highlighted in blue) was set to contain another variable concatenated with the ufy variable at the end. This means the string contained in iioi655er5w5 ends in .exe. The function FileOutputStream writes data to a file and names the file with the string in the iioi655er5w5 variable.

The previous code explains the activity on the system immediately after the exploit was downloaded. Reading the URL hxxp://www.seyminck.com/FFFO009/560[dot]gif resulted in Java caching the file while Java wrote the data to a file with an .exe file extension. The Java index file 25e8c780-5c17647b.idx showed that the file 46e770f3-38b55d85 (MD5 hash 2e833ac26483aaad13a8051bc857ef15) in the Java cache was read from the URL in the Java exploit. Another file with the same MD5 hash was created on the system at the same time and was named a random number with exe as the file extension.

At the bottom of the previous screenshot shows the Java method Kkdjfhgdkfjhgkdfjhgkkkkkkkkkkkk.kjsf8888 being called and the variable iioi655er5w5 (contains the filename ending in .exe) is passed for the method to use. The picture below is a close up of the method call.

My journey following the code ended when I went to the kjsf8888 method in the Kkdjfhgdkfjhgkdfjhgkkkkkkkkkkkk class file. The code highlighted in green in the picture below highlights the function Runtime exec executing the file contained in the iioi655er5w5 variable which is a file whose name is random number with an .exe extension (seems like this file 0.945837921339929.exe found on the system). The activity on the system after 0.945837921339929.exe was created in the temp folder was another dropper (MD5 hash a70e5c48612159b3e936d7e478f4d451) showing up on the system. To me this further confirms the Jar file was successful in exploiting a vulnerability in Java and this was how the system became infected in the first place.

Summary

I went into the examination planning on to perform a surgical malware removal and ended up doing a complete system rebuild due to how bad the infection was. The initial infection vector was a user surfing the Internet and coming across a website hosting third party content which resulted in a successful drive-by download targeting some Java vulnerability. Going back to the person and telling them how the infection happened makes it easier for them to change what lead up to the issue. I would have done a disservice if I skipped trying to find the IIV and went back to the person with a laundry list of recommendations. Enable the firewall, use strong passwords, update anti-virus software, use caution with opening attachments, use caution clicking on links, update computer software, etc … Throwing out a laundry list of recommendations is a lost opportunity to improve security since it doesn’t address the root cause. Trying to implement five or ten recommendations is a lot harder than focusing on the one recommendation that actual caused the infection.

Identifying the IIV is a challenge worth confronting. For success one not only needs to understand the forensic artifacts located on a system and their significance but needs to know about attack vector artifacts and how to recognize them. Being able to understand both artifacts types can help in answering the question how did malware end up on the system.

When I’m looking at conferences and trainings the cost is one of the top two things I consider. This is especially true if I’m going to ask my employer to pick up the tab. Similar to other organizations it is extremely hard to get travel approved through my organization. As a public sector employee at times it seems like I’d have better odds getting someone’s first born then to get a request approved through the finance office. The low cost to attend PFIC made it easier for me to get people to sign off on it. The conference with one day training was only $400. The location was the Canyons Resort and attendees got cheaper rates for lodging since it’s the off-season. Rounding out the price tag were the plane flight and shuttle from the airport; both expenses were fairly reasonable. Don’t be fooled by the low costs thinking PFIC is the equivalent of a fast food restaurant while the other conferences are fine dining. PFIC is not only an economical choice but the content covered in the bootcamp and sessions results in more bang for the buck. I like to think PFIC is the equivalent of fine dining with coupons. The cost was so reasonable that I was even going to swing the conference by myself if my employer denied my request to attend. That’s how much value I saw in the price tag especially when I compared it to other DFIR conferences.

Networking Opportunities

The one commonality I’ve see in other’s feedback about PFIC is how the smaller conference size provides opportunities to network with speakers and other practitioners. This was my first DFIR conference so I can’t comment about conference sizes. However, I agree about the ability to talk with people from the field. Everyone was approachable during the conference without having to wait for crowds to disperse. Plus if for some reason you were unable to connect between sessions then PFIC had evening activities such as casino night and night out in town. I meet some great people at the conference and was finally able to meet a few people I only talked to online. Going into the conference I underestimated the value in connecting with others since I was so focused on the content.

Content

Let’s be honest. A conference can be affordable and offer great networking opportunities but if the content is not up to par then the conference will be a waste of time and money. I have a very simple way to judge content; it should benefit my work in some way. This means none of the following would fit the bill: academics discussing interesting theories which has no relevance to my cases, vendors pimping some product as the only way to solve an issue, or presenters discussing a topic at such a high level there is no useful information I can apply to my work. One thing I noticed about the PFIC presenters was they are practitioners in the field discussing techniques and tools they used to address an issue. Pretty much each session I walked away from I felt like I learned a few useful things and got a few ideas to research further. Harlan said in his PFIC 2011 post that “there were enough presentations along a similar vein that you could refer back to someone else's presentation in order to add relevance to what you were talking about”. I think the same thing can be said from the attendee’s perspective. I sat through several presentations on incident response and mobile devices and it seemed as if the presentations built on one another.

I pretty much picked my sessions on a topic I wanted to know more about (incident response) and another topic I wanted to get exposed to (mobile devices). There were a few presentations I picked based on the presenter but for the most part my focus was on incident response and mobile devices. PFIC had a lot more to offer including e-discovery, legal issues, and digital forensics topics but I decided to focus on two specific topics. In the end I’m glad I did since each presentation discussed a different area about the topic which gave me a better understanding. I’m not discussing every session I attended but I wanted to reflect on a few.

Incident Response

I started PFIC by attending the Incident Response bootcamp taught by Ralph Gorgal. The overview about the process used in the session is shown below and the activities highlighted in red is what the bootcamp focused on (everything to the right of the arrows are my notes about the activity).

The approach taken was for us to simulate walking in to a network and trying to understand the network and what logs were available to us. To accomplish that we reviewed servers’ configurations including the impact different configuration settings have and identified where the servers where storing their logs. The Windows services explored during the bootcamp were: active directory, terminal services, internet information server (IIS), exchange, SQL, and ISA. The focus was more on following a logical flow through the network (I thought it was similar to the End to End Digital Investigation) and thinking about what kind of evidence is available and where it was located.

The bootcamp provided a thorough explanation about the thought process behind conducting log analysis during incident response. Even though the course didn’t touch on how to perform the log analysis other sessions offered at PFIC filled in the void. The first session was We’re infected, now what? How can logs provide insight? presented by David Nardoni and Tomas Castrejon. The session started out by first explaining what logs are, breaking down the different types of logs (network, system, security, and application), and explaining what the different log types can tell you. The rest of the session focused on using the free tools Splunk and Mandiant’s Highlighter to examine firewall and Windows event logs. I thought the presentation was put together well and the hands on portion examining actual logs reinforced the information presented to us. The other session I attended about log analysis was Log File Analysis in Incident Response presented by Joe McManus. The presentation was how web server and proxy logs can generate leads about an incident by using the open source tool Log Analysis Tool Kit (LATK). LATK helps to automate the process of log analysis by quickly showing log indicators such as top downloaders/uploaders, SQL queries, and vulnerable web page access. The session was a lab and in the hands on portion we examined web server and proxy logs. This was another session that was well put together and I think the coolest thing about both sessions, besides the great information shared, was that free tools were used to perform log analysis.

Mobile Devices

Mobile devices are a topic I want to become more knowledgeable about. I went into PFIC wanting to learn a basic understanding about the forensic value contained in mobile devices and get some hands on experience examining them.

The first of the three Paraben labs I attended was Smartphone and Tablet Forensic Processing by Amber Schroader. This wasn’t my scheduled lab so I watched from the back as others did the hands on portion. Amber laid out a case study for the attendees who had to locate a missing 15 year old girl by using Device Seizure to examine an ipad and itouch. What I liked about the session was that answers weren’t provided to the audience which forced them to have to figure out what information on those devices could help locate the girl. A few of the areas examined included: Safari browsing history, Safari download history, Youtube history, facetime history, wifi locations, and pictures. After the case study Amber laid out the different areas on mobile devices containing relevant information but mentioned the biggest issue with mobiles is the sheer number of apps which changes how you look at your data. The next Paraben lab I sat through was Physical Acquisitions of Mobiles by Diane Barrett. The session explained the different methods to acquire a physical image which were chip off, JTAG test access port, flasher boxes, and logical software that can do physical. The cool part about the session was the hands on portion since we used a Tornado flasher box and Device Seizure to acquire a physical image from a Motorola phone. The last Paraben lab I attended was Introduction to Device Seizure by Amber Schroader and Eric Montellese. As the title indicates the session was an introduction on how device seizure can be used to examine mobile devices. The entire session was pretty much hands on; we performed logical and physical acquisitions of a Motorola phone and a logical acquisition of an Android. We also briefly examined both devices to see what information was available.

The only non-Paraben session about mobile devices I attended was iOS Forensics by Ben Lemere. The presentation discussed how to perform forensics on iOS devices using free tools. The information provided was interesting and added to my to-do list but I thought the session would have been better if it was a lab. It would have been awesome to try out the stuff the presenter was talking about.

Digital Forensic Topics

I couldn’t come up with a better description than Digital Forensics Topics for the sessions I picked based on the presenter or topic. The one session I wanted to mention in this category was Scanning for Low Hanging Fruit in an Investigation by Harlan Carvey. I was really interested in attending Harlan’s session so I could finally see the forensic scanner he has been talking about. Out of all of the sessions I attended I think this was the only session where I knew about the topic being discussed (I follow Harlan’s blog and he has been discussing his forensic scanner). Harlan explained how the scanner is an engine that runs a series of checks searching for low hanging fruit (known artifacts on the system). The usage scenario he laid out involves:

Harlan mentioned the scanner is still in development but he still did a tool demo by parsing a system’s Windows folder. A few things I noted about what I saw: there’s better documentation than Regripper (analysts name and platform included), still rips registry keys, lists files in a directory (prefetch folder contents were showed), runs external programs (evt.pl was executed), hashes files, and performs different file checks. I saw the value in this kind of tool before I sat through the session but seeing it in action reinforces how valuable this capability would be. I currently try to mimic some activities with batch scripting (see my triage post or obtaining information post). Those scripts took some time to put together and would require some work to make them do something else. I can foresee the forensic scanner handling this in a few seconds since plugins would just need to be selected; plus the scanner can do stuff that's impossible with batch scripting.

Speaking of scripts … Harlan mentioned during his presentation a batch script I put together that runs Regripper across every volume shadow copy (VSC) on a system. I was caught a little off guard since I'd never imagined Harlan mentioning my work during his presentation. I probably didn’t do a good job explaining the script during the session since I wasn’t expecting to talk about it. Here is some information about the script. As Harlan mentioned, I added functionality to the script besides running Regripper (I still have a standalone script for Regripper in case anyone doesn’t want the other functions). The script can identify the differences between VSCs, hash files in VSCs, extract data (preserves timestamps and NTFS permissions) from VSCs, and list files in the VSC. The script demonstrates that you can pretty much do as you please with VSCs whether if you are examining a forensic image or live system. In a few weeks I’ll provide a little more information about the script and why I wrote it, and over the next few months I’ll write a series of posts explaining the logic behind the script before I release it.

PFIC Summary

Overall PFIC was a great experience. I learned a lot of information, I have a to-do list outlining the various things to research/test further, and I meet some great people. The return on investment for my company sending me to the conference is that in a few weeks I’ll be able to perform log analysis, I’m more knowledgeable about mobile device forensics, and if I get into a jam I now have a few people I can reach out to for help.

Closing out my post I wanted to share a few thoughts for improvement. I didn’t have many which I guess is a good thing. ;)

1. Make the names on the name tags bigger. I think my biggest struggle during the conference was trying to figure out peoples’ names since I couldn’t read the tags.

2. Presenters should answer all questions during the session if time permits; especially if the question is a follow-up to something the presenter said. Another attendee asked a great question but I had to stick around for about five minutes after the session to hear the answer. It wasn’t like the question was controversial or something.

3. Verify that all equipment works before the session. One of the labs hit a speed bump when numerous attendees (me included) couldn’t acquire a phone since numerous phones didn’t work. Everyone was able to do the acquisition eventually but time was lost trying to find phones that actually worked.